Introductory probabilistic and stochastic analysis and design of circuits

1993 ◽  
Vol 36 (1) ◽  
pp. 51-56 ◽  
Author(s):  
W.F. Curi ◽  
K. Ponnambalam
Keyword(s):  
Stochastic Analysis ◽  
Analysis And Design

SAMS: Stochastic Analysis With Minimal Sampling—A Fast Algorithm for Analysis and Design Under Uncertainty

2004 ◽  
Vol 127 (4) ◽  
pp. 558-571 ◽  
Author(s):  
A. Mawardi ◽  
R. Pitchumani
Keyword(s):  
System Performance ◽  
Stochastic Analysis ◽  
Sampling Method ◽  
Latin Hypercube Sampling ◽  
Analysis And Design ◽  
Process Outcomes ◽  
Input Parameters ◽  
Computationally Intensive ◽  
Uncertain Input ◽  
Reliability And Robustness

Design of processes and devices under uncertainty calls for stochastic analysis of the effects of uncertain input parameters on the system performance and process outcomes. The stochastic analysis is often carried out based on sampling from the uncertain input parameters space, and using a physical model of the system to generate distributions of the outcomes. In many engineering applications, a large number of samples—on the order of thousands or more—is needed for an accurate convergence of the output distributions, which renders a stochastic analysis computationally intensive. Toward addressing the computational challenge, this article presents a methodology of S̱tochastic A̱nalysis with M̱inimal S̱ampling (SAMS). The SAMS approach is based on approximating an output distribution by an analytical function, whose parameters are estimated using a few samples, constituting an orthogonal Taguchi array, from the input distributions. The analytical output distributions are, in turn, used to extract the reliability and robustness measures of the system. The methodology is applied to stochastic analysis of a composite materials manufacturing process under uncertainty, and the results are shown to compare closely to those from a Latin hypercube sampling method. The SAMS technique is also demonstrated to yield computational savings of up to 90% relative to the sampling-based method.

Partial Stochastic Linearization of a Spherical Pendulum With Coriolis Damping Produced by Radial Spring and Damper

2015 ◽  
Vol 137 (5) ◽  
Author(s):  
L. D. Viet
Keyword(s):  
Numerical Simulation ◽  
Stochastic Analysis ◽  
Radial Direction ◽  
Spherical Pendulum ◽  
Analysis And Design ◽  
Partial Linearization ◽  
System A ◽  
Stochastic Linearization ◽  
Linearized System ◽  
Sway Motion

This study considers the stochastic analysis of a spherical pendulum, whose bidirectional vibration is reduced by spring and damper installed in the radial direction between the point mass and the cable. Under sway motion, the centrifugal force results in the radial motion, which in its turn produces the Coriolis force to reduce sway motion. In stochastic analysis and design, the problem is that the Monte Carlo simulation is time-consuming, while the full stochastic linearization totally fails to describe the effectiveness of the spring and damper. We propose the partial linearization applied to the Coriolis damping to overcome the disadvantages of two mentioned methods. Moreover, the proposed technique can give the analytical solution of partial linearized system. A numerical simulation is performed to verify the proposed approach.

Stochastic Analysis and Design of Systems

2011 ◽  
Author(s):  
George A. Mathew ◽  
Alessandro Pinto
Keyword(s):  
Stochastic Analysis ◽  
Analysis And Design

Cardiological Database Management System as a Mediator to Clinical Decision Support

1996 ◽  
Vol 35 (01) ◽  
pp. 52-58 ◽  
Author(s):  
A. Mavromatis ◽  
N. Maglaveras ◽  
A. Tsikotis ◽  
G. Pangalos ◽  
V. Ambrosiadou ◽  
...  
Keyword(s):  
Management System ◽  
Database Management ◽  
Medical Information ◽  
Object Oriented ◽  
Medical Personnel ◽  
Database Management System ◽  
Ease Of Use ◽  
Medical Database ◽  
Analysis And Design ◽  
Object Oriented Design

AbstractAn object-oriented medical database management system is presented for a typical cardiologic center, facilitating epidemiological trials. Object-oriented analysis and design were used for the system design, offering advantages for the integrity and extendibility of medical information systems. The system was developed using object-oriented design and programming methodology, the C++ language and the Borland Paradox Relational Data Base Management System on an MS-Windows NT environment. Particular attention was paid to system compatibility, portability, the ease of use, and the suitable design of the patient record so as to support the decisions of medical personnel in cardiovascular centers. The system was designed to accept complex, heterogeneous, distributed data in various formats and from different kinds of examinations such as Holter, Doppler and electrocardiography.

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